An integrated model for designing and optimising an international logistics network

Creazza, Alessandro; Dallari, Fabrizio; Rossi, Tommaso

Abstract

Supply-chain configuration has recently gained increasing attention both from the practitioner’s perspective and as a research area. This paper proposes an integrated model for designing and optimising international logistics networks. It consists of a mixed integer linear programming model and a data-mapping section (i.e. methodological guidelines for gathering and processing the data necessary to set up the model). It has been specifically developed for solving the configuration problem for supply chains characterised by a complexity level typical of real-life global logistics networks. Although this topic is well understood and well elaborated at a technical level in the extant literature, it still presents obstacles in practice especially in terms of dealing with real-life complexity, service-level constraints and data mapping. Thus, we developed our integrated approach with the aim to fill these gaps. We designed our model for dealing with multiple-layer, single location-layer, multiple-commodity and time-constrained logistics networks, to be implemented in a single period time horizon and in a deterministic environment. The proposed approach represents an innovative contribution to the existing body of scientific knowledge and facilitates the data gathering and processing activities, which are largely recognised as complex and time-consuming processes for the management of logistics activities.

Citation

Creazza, A., Dallari, F., & Rossi, T. (2012). An integrated model for designing and optimising an international logistics network. International Journal of Production Research, 50(11), 2925-2939. https://doi.org/10.1080/00207543.2011.578157

• Publication Date: 2012-06
• Deposit Date: Nov 13, 2014
• Publicly Available Date: Nov 23, 2017
• Journal: International journal of production research
• Print ISSN: 0020-7543
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 50
• Issue: 11
• Pages: 2925-2939
• DOI: https://doi.org/10.1080/00207543.2011.578157
• Keywords: Management Science and Operations Research; Strategy and Management; Industrial and Manufacturing Engineering
• Public URL: https://hull-repository.worktribe.com/output/470403
• Publisher URL: http://www.tandfonline.com/doi/figure/10.1080/00207543.2011.578157?scroll=top&needAccess=true
• Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 15th July 2011, available online: http://wwww.tandfonline.com/10.1080/00207543.2011.578157
• Contract Date: Nov 23, 2017